A revised model of energy transactions and body composition in sheep.

A mechanistic, dynamic model was developed to calculate body composition in growing lambs by calculating heat production (HP) internally from energy transactions within the body. The model has a fat pool (f) and three protein pools: visceral (v), nonvisceral (m), and wool (w). Heat production is calculated as the sum of fasting heat production, heat of product formation (HrE), and heat associated with feeding (HAF). Fasting heat production is represented as a function of visceral and nonvisceral protein mass. Heat associated with feeding (HAF) is calculated as ((1 - km) x MEI), where km is partial efficiency of ME use for maintenance, and MEI = metabolizable energy intake) applies at all levels above and below maintenance. The value of km derived from data where lambs were fed above maintenance was 0.7. Protein change (dp/dt) is the sum of change in the m, v, and w pools, and change in fat is equal to net energy available for gain minus dp/dt. Heat associated with a change in body composition (HrE) is calculated from the change in protein and fat with estimated partial efficiencies of energy use of 0.4 and 0.7 for protein and fat, respectively. The model allows for individuals to gain protein while losing fat or vice versa. When evaluated with independent data, the model performed better than the current Australian feeding standards (Freer et al., 2007) for predicting protein gain in the empty body but did not perform as well as for gain of fat and fleece-free empty body weight. Models performed similarly for predicting clean wool growth. By explicit representation of the major energy using processes in the body, and through simplification of the way body composition is computed in growing animals, the model is more transparent than current feeding systems while achieving similar performance. An advantage of this approach is that the model has the potential for wider applicability across different growth trajectories and can explicitly account for the effects of systematic changes on energy transactions, such as the effects of selective breeding, growth manipulation, or environmental changes.

Based on prior work by Oltjen et al. (2006), a revised dynamic, mechanistic model was developed to improve the prediction of the composition of protein and fat in the body of growing ruminants. The revised model calculates heat production (HP) internally as a function of fasting HP, heat associated with feeding, and HP from changes in fat and protein within the body. Heat associated with product formation is calculated from changes in body protein and fat, with separate efficiencies for each, while heat associated with feeding is a constant proportion of metabolizable energy intake and applies at all levels of feeding above and below maintenance. When evaluated against novel data, the revised model performed similarly to current Australian feeding standards (Freer et al., 2007) Unlike the Freer model, the revised model captures variation in HP arising from feed as well as gain of protein and fat. The revised model explicitly represents protein in the body as two pools with markedly different rates of energy expenditure, improving representation of the underlying biology compared to current feeding systems. This provides a more flexible way to predict energy requirements and body composition in growing animals while achieving similar performance to current feeding systems.

How advances in animal efficiency and management have affected beef cattle's water intensity in the United States: 1991 compared to 2019.

Updating the static model by Beckett and Oltjen (1993), we determined that from 1991 to 2019, U.S. beef cattle blue water consumption per kg of beef decreased by 37.6%. Total water use for the U.S. cattle herd decreased by 29%. As with the 1993 model, blue water use included direct water intake by animals, water applied for irrigation of crops that were consumed by beef cattle, water applied to irrigated pasture, and water used to process animals at marketing. Numbers of cattle, crop production, and irrigation data were used from USDA census and survey data. On 1 January 2019, a total of 31.7-million beef cows and 5.8-million replacement heifers were in U.S. breeding herds, and 26-million animals were fed annually. In total, the U.S. beef cattle herd (feedlot and cull cows) produced 7.7-billion kg of boneless beef, an increase of 10% since 1991. Beef cattle directly consumed 599-billion L of water per year. Feedlot cattle were fed various grain and roughage sources corresponding to the regions in which they were fed. Feeds produced in a state were preferentially used by cattle in that state with that state's efficiency; any additional feedstuffs required used water at the national efficiency. Irrigation of crop feedstuffs for feedlot cattle required 5,920-billion L of water. Irrigated pasture for beef cattle production required an additional 4,121-billion L of water. Carcass processing required 91-billion L of water. The model estimated that in the U.S. 2,275 L of blue water was needed to produce 1 kg of boneless meat. As with the previous model, the current model was most sensitive to changes in the dressing percentage and the percentage of boneless yield in carcasses of feedlot cattle (62.8 and 65, respectively). In conclusion, with more beef, fewer cows, and lower rates of irrigation, beef cattle's water intensity has decreased at an annual rate of 1.34% over a 28-yr period.

In 1993, Beckett and Oltjen published an innovative model that evaluated beef cattle's blue water (ground water and surface water) use in the United States. The model stated that to produce one lb. of boneless beef, 440 gallons of blue water were required. Although this model shifted the prevailing acumen regarding beef cattle's water use and became the fifth most cited Journal of Animal Science article in popular press, with today's vast changes in cattle genetics, animal management, and irrigation practices, the value generated in this model has become obsolete. By updating Beckett and Oltjen (1993) with today's agricultural inputs, the present model was the first to use an "apples to apples" strategy to compare beef cattle's blue water use over time. Utilizing USDA irrigation and cattle inventory datasets along with expertise from university extension, the current model determined that over a 28-yr period beef cattle's water intensity per one lb. of boneless beef was 275 gallons, a decrease of 38%. In addition, total water use for the U.S. beef production system decreased by 29%. The principal reasons for these decreases were due to the decrease in water used to irrigate crops and pasture, increased meat per carcass, and improved efficiencies in cattle management and nutrition. Despite these decreases in water use and intensity, water will continue to be a concern for beef cattle production, particularly in the west where surface and ground water are rapidly depleting. The beef industry has made great strides in water reduction but will need to continue to decrease blue water use, for if there is no water, beef cannot be produced.

Evaluating the Shelf Life and Sensory Properties of Beef Steaks from Cattle Raised on Different Grass Feeding Systems in the Western United States.

Consumer interest in grass-fed beef has been steadily rising due to consumer perception of its potential benefits. This interest has led to a growing demand for niche market beef, particularly in the western United States. Therefore, the objective of this study was to assess the impact of feeding systems on the change in microbial counts, color, and lipid oxidation of steaks during retail display, and on their sensory attributes. The systems included: conventional grain-fed (CON), 20 months-grass-fed (20GF), 25-months-grass-fed (25GF) and 20-months-grass-fed + 45-day-grain-fed (45GR). The results indicate that steaks in the 20GF group displayed a darker lean and fat color, and a lower oxidation state than those in the 25GF group. However, the feeding system did not have an impact on pH or objective tenderness of beef steaks. In addition, consumers and trained panelist did not detect a difference in taste or flavor between the 20GF or 25GF steaks but expressed a preference for the CON and 45GR steaks, indicating that an increased grazing period may improve the color and oxidative stability of beef, while a short supplementation with grain may improve eating quality.

Effects of dietary energy density and supplemental rumen undegradable protein on intake, viscera, and carcass composition of lambs recovering from nutritional restriction.

Variation in nutrition is a key determinant of growth, body composition, and the ability of animals to perform to their genetic potential. Depending on the quality of feed available, animals may be able to overcome negative effects of prior nutritional restriction, increasing intake and rates of tissue gain, but full compensation may not occur. A 2 × 3 × 4 factorial serial slaughter study was conducted to examine the effects of prior nutritional restriction, dietary energy density, and supplemental rumen undegradable protein (RUP) on intake, growth, and body composition of lambs. After an initial slaughter (n = 8), 124 4-mo-old Merino cross wethers (28.4 ± 1.8 kg) were assigned to either restricted (LO, 500 g/d) or unrestricted (HI, 1500 g/d) intake of lucerne and oat pellets. After 8 wk, eight lambs/group were slaughtered and tissue weights and chemical composition were measured. Remaining lambs were randomly assigned to a factorial combination of dietary energy density (7.8, 9.2, and 10.7 MJ/kg DM) and supplemental RUP (0, 30, 60, and 90 g/d) and fed ad libitum for a 12- to 13-wk experimental period before slaughter and analysis. By week 3 of the experimental period, lambs fed the same level of energy had similar DMI (g/d) and MEI (MJ/d) (P > 0.05), regardless of prior level of nutrition. Restricted-refed (LO) lambs had higher rates of fat and protein gain than HI lambs (P < 0.05) but had similar visceral masses (P > 0.05). However, LO lambs were lighter and leaner at slaughter, with proportionally larger rumens and livers (P < 0.05). Tissue masses increased with increasing dietary energy density, as did DMI, energy and nitrogen (N) retention (% intake), and rates of protein and fat gain (P < 0.05). The liver increased proportionally with increasing dietary energy density and RUP (P < 0.05), but rumen size decreased relative to the empty body as dietary energy density increased (P < 0.05) and did not respond to RUP (P > 0.05). Fat deposition was greatest in lambs fed 60 g/d supplemental RUP (P < 0.05). However, lambs fed 90 g/d were as lean as lambs that did not receive supplement (P0, P > 0.05), with poorer nitrogen retention and proportionally heavier livers than P0 lambs (P < 0.05). In general, visceral protein was the first tissue to respond to increased intake during refeeding, followed by non-visceral protein and fat, highlighting the influence of differences in tissue response over time on animal performance and body composition.

Animal performance is determined by the combined effects of both prior and current nutrition. The present study used a 2 × 3 × 4 factorial to examine the effects of prior feeding level (HI or LO) on subsequent ad-libitum intake of diets varying in energy density (7.8, 9.2, 10.7 MJ/kg DM) and level of supplemental rumen undegradable protein (RUP; 0, 30, 60, and 90g/d). By week 3 of refeeding, LO and HI lambs had similar feed intake, but LO lambs had proportionally more gut and liver tissue and were lighter and leaner at final slaughter. As dietary energy density increased, the rumen became proportionally smaller while the liver became proportionally larger. Liver size increased with increasing RUP, and lambs fed 30 and 60 g/d were fatter than other lambs. However, lambs fed 90 g/d RUP had less fat than other lambs, as the increased energy requirements of a larger liver and of disposing of excess nitrogen appeared to outweigh any nutritional benefits. Understanding how prior nutrition affects current performance, as well as how tissues vary in their response to the same diet, is key to improving our understanding of animal performance and response to change.

Grass-fed vs. grain-fed beef systems: performance, economic, and environmental trade-offs.

Between increasing public concerns over climate change and heightened interest of niche market beef on social media, the demand for grass-fed beef has increased considerably. However, the demand increase for grass-fed beef has raised many producers' and consumers' concerns regarding product quality, economic viability, and environmental impacts that have thus far gone unanswered. Therefore, using a holistic approach, we investigated the performance, carcass quality, financial outcomes, and environmental impacts of four grass-fed and grain-fed beef systems currently being performed by ranchers in California. The treatments included 1) steers stocked on pasture and feedyard finished for 128 d (CON); 2) steers grass-fed for 20 mo (GF20); 3) steers grass-fed for 20 mo with a 45-d grain finish (GR45); and 4) steers grass-fed for 25 mo (GF25). The data were analyzed using a mixed model procedure in R with differences between treatments determined by Tukey HSD. Using carcass and performance data from these systems, a weaning-to-harvest life cycle assessment was developed in the Scalable, Process-based, Agronomically Responsive Cropping Systems model framework, to determine global warming potential (GWP), consumable water use, energy, smog, and land occupation footprints. Final body weight varied significantly between treatments (P < 0.001) with the CON cattle finishing at 632 kg, followed by GF25 at 570 kg, GR45 at 551 kg, and GF20 478 kg. Dressing percentage differed significantly between all treatments (P < 0.001). The DP was 61.8% for CON followed by GR45 at 57.5%, GF25 at 53.4%, and GF20 had the lowest DP of 50.3%. Marbling scores were significantly greater for CON compared to all other treatments (P < 0.001) with CON marbling score averaging 421 (low-choice ≥ 400). Breakeven costs with harvesting and marketing for the CON, GF20, GR45, and GF25 were $6.01, $8.98, $8.02, and $8.33 per kg hot carcass weight (HCW), respectively. The GWP for the CON, GF20, GR45, and GF25 were 4.79, 6.74, 6.65, and 8.31 CO2e/kg HCW, respectively. Water consumptive use for CON, GF20, GR45, and GF25 were 933, 465, 678, and 1,250 L/kg HCW, respectively. Energy use for CON, GF20, GR45, and GF25 were 18.7, 7.65, 13.8, and 8.85 MJ/kg HCW, respectively. Our results indicated that grass-fed beef systems differ in both animal performance and carcass quality resulting in environmental and economic sustainability trade-offs with no system having absolute superiority.

Between the influence of the "food elite" on social media and increasing public concerns over climate change, consumer demand for grass-fed beef has increased considerably. Although many consumers perceive grass-fed beef as more environmentally friendly than grain-fed beef, there is a dearth of research available to address these consumer claims. In order to answer both consumer and producer concerns, we performed an experiment that evaluated the environmental footprint (i.e., water, land, greenhouse gasses, and energy), beef quality, and economic outcome of four beef cattle production systems on the West coast. The four systems included conventional beef finished on grain for 128 d, steers grass-fed for 20 mo, steers grass-fed for 20-mo with a 45-d grain finish, and steers grass-fed for 25 mo. We found that varying grass-fed and grain-fed production systems resulted in different environmental effects. The conventional system produced the lowest greenhouse gas footprint but required the highest energy input. The grass-fed for 20 mo used the least amount of water but produced the greatest greenhouse gas. In conclusion, this study illustrated the complexities underpinning beef sustainability; no system resulted in absolute economic, meat quality, and environmental superiority.

Effects of feeding level on efficiency of high- and low-residual feed intake beef steers.

Comparing heat production after ad libitum (ADLIB) and restricted (RESTRICT) feeding periods may offer insight into how residual feed intake (RFI) groups change their energy requirements based on previous feeding levels. In this study, the authors sought to explain the efficiency changes of high- and low-RFI steers after feed restriction. To determine RFI classification, 56 Angus-cross steers with initial body weight (BW) of 350 ± 28.7 kg were individually housed, offered ad libitum access to a total mixed ration, and daily intakes were recorded for 56 d. RFI was defined as the residual of the regression of dry matter intake on mid-test BW0.75 and average daily gain. High- and low-RFI groups were defined as >0.5 SD above or below the mean of zero, respectively. Fourteen steers from each high and low groups (n = 28) were selected for the subsequent 56-d RESTRICT period. During the RESTRICT period, intake was restricted to 75% of previous ad libitum intake on a BW0.75 basis, and all other conditions remained constant. After the RESTRICT period, both RFI groups had decreased maintenance energy requirements. However, the low-RFI group decreased maintenance energy requirements by 32% on a BW0.75 basis, more (P < 0.05) than the high-RFI group decreased maintenance requirements (18%). Thus, the low-RFI steers remained more efficient after a period of feed restriction. We conclude that feed restriction decreases maintenance energy requirement in both high- and low-RFI groups that are restricted to the same degree.

Monensin and mineral supplementation economically increase yearling cattle weight gain on California annual rangeland.

Stocker operators generally graze cattle on California annual rangelands from November to May. The profit margins of these operators is low as cattle sell for less per unit at the end of the season when compared with the beginning. This creates a need for methods to economically increase weight gain, which can help to mitigate market volatility. The use of monensin is common in much of the United States but has not been researched in the unique winter annual rangelands of California. Likewise, research that formally documents weight gain from the correction of selenium deficiency on these rangelands is also lacking. Trials were conducted over 2 years to determine weight gain differences with treatments of salt only (control), salt with monensin, mineral supplement, and mineral supplement with monensin. All three treatments increased weight gain by 12%, 9%, and 15% over feeding straight salt, respectively. It appears that selenium deficiency correction and supplemental monensin should be considered economical weight gain improvement tools for yearling cattle grazing California annual rangeland.

How did Lofgreen and Garrett do the math?

Lofgreen and Garrett introduced a new system for predicting growing and finishing beef cattle energy requirements and feed values using net energy concepts. Based on data from comparative slaughter experiments they mathematically derived the California Net Energy System. Scaling values to body weight to the ¾ power, they summarized metabolizable energy intake (ME), energy retained (energy balance [EB]), and heat production (HP) data. They regressed the logarithm of HP on ME and extended the line to zero intake, and estimated fasting HP at 0.077 Mcal/kg0.75, similar to previous estimates. They found no significant difference in fasting HP between steers and heifers. Above maintenance, however, a logarithmic fit of EB on ME does not allow for increased EB once ME is greater than 340 kcal/kg0.75, or about three times maintenance intake. So based on their previous work, they used a linear fit so that partial efficiency of gain above maintenance was constant for a given feed. They show that with increasing roughage level efficiency of gain (slope) decreases, consistent with increasing efficiency of gain and maintenance with greater metabolizable energy of the feed. Making the system useful required that gain in body weight be related to EB. They settled on a parabolic equation, with significant differences between steers and heifers. Lofgreen and Garrett also used data from a number of experiments to relate ME and EB to estimate the ME required for maintenance (ME = HP) and then related the amount of feed that provided that amount of ME to the metabolizable energy content of the feed (MEc), resulting in a logarithmic equation. Then they related that amount of feed to the net energy for gain calculated as the slope of the EB line when regressed against feed intake. Combining the two equations, they estimate the net energy for maintenance and gain per unit feed (Mcal/kg dry matter) as a function of MEc: 0.4258 × 1.663MEc and 2.544-5.670 × 0.6012MEc, respectively. Finally, they show how to calculate net energy for maintenance and gain from experiments where two levels of a ration are fed and EB measured, where one level is fed and a metabolism trial is conducted, or when just a metabolism trial is conducted-but results are not consistent between designs.

Carbon and blue water footprints of California sheep production.

While the environmental impacts of livestock production, such as greenhouse gas emissions and water usage, have been studied for a variety of US livestock production systems, the environmental impact of US sheep production is still unknown. A cradle-to-farm gate life cycle assessment (LCA) was conducted according to international standards (ISO 14040/44), analyzing the impacts of CS representing five different meat sheep production systems in California, and focusing on carbon footprint (carbon dioxide equivalents, CO2e) and irrigated water usage (metric ton, MT). This study is the first to look specifically at the carbon footprint of the California sheep industry and consider both wool and meat production across the diverse sheep production systems within California. This study also explicitly examined the carbon footprint of hair sheep as compared with wooled sheep production. Data were derived from producer interviews and literature values, and California-specific emission factors were used wherever possible. Flock outputs studied included market lamb meat, breeding stock, 2-d-old lambs, cull adult meat, and wool. Four different methane prediction models were examined, including the current IPCC tier 1 and 2 equations, and an additional sensitivity analysis was conducted to examine the effect of a fixed vs. flexible coefficient of gain (kg) in mature ewes on carbon footprint per ewe. Mass, economic, and protein mass allocation were used to examine the impact of allocation method on carbon footprint and water usage, while sensitivity analyses were used to examine the impact of ewe replacement rate (% of ewe flock per year) and lamb crop (lambs born per ewe bred) on carbon footprint per kilogram market lamb. The carbon footprint of market lamb production ranged from 13.9 to 30.6 kg CO2e/kg market lamb production on a mass basis, 10.4 to 18.1 kg CO2e/kg market lamb on an economic basis, and 6.6 to 10.1 kg CO2e/kg market lamb on a protein mass basis. Enteric methane (CH4) production was the largest single source of emissions for all CS, averaging 72% of total emissions. Emissions from feed production averaged 22% in total, primarily from manure emissions credited to feed. Whole-ranch water usage ranged from 2.1 to 44.8 MT/kg market lamb, almost entirely from feed production. Overall results were in agreement with those from meat-focused sheep systems in the United Kingdom as well as beef raised under similar conditions in California.